## Rows: 11,932
## Columns: 14
## $ enrlmt_id <chr> "I20031103000394", "I20031104000436", "I2003…
## $ npi <int> 1790853083, 1356302715, 1356302715, 13564367…
## $ pecos_asct_cntl_id <dbl> 1254243868, 6507778826, 6507778826, 95370718…
## $ provider_type_desc.before <chr> "PRACTITIONER - FAMILY PRACTICE", "PRACTITIO…
## $ state_cd.before <chr> "CA", "PA", "PA", "FL", "FL", "FL", "FL", "F…
## $ first_name <chr> "CORINNE", "PATRICK", "PATRICK", "HUMBERTO",…
## $ mdl_name <chr> "VIVIAN", "T", "T", "R", "R", "R", "R", "R",…
## $ last_name <chr> "BASCH", "WATERS", "WATERS", "FERNANDEZ MIRO…
## $ gndr_sw <chr> "Female", "Male", "Male", "Male", "Male", "M…
## $ city_name <chr> "ARCATA", "HUNTINGDON VALLEY", "HUNTINGDON V…
## $ zip_code <chr> "95521", "19006", "19006", "33136", "33013",…
## $ rcv_bnft_enrlmt_id <chr> "O20040121001146", "O20050419000796", "O2018…
## $ provider_type_desc.after <chr> "PRACTITIONER - GENERAL PRACTICE", "PRACTITI…
## $ state_cd.after <chr> "CA", "PA", "PA", "FL", "FL", "FL", "FL", "F…
Analyze how telemedicine-capable providers are distributed across geographic regions on sample data.
## # A tibble: 53 × 2
## state_cd.before provider_count
## <chr> <int>
## 1 AK 7
## 2 AL 97
## 3 AR 78
## 4 AZ 208
## 5 CA 2806
## 6 CO 45
## 7 CT 53
## 8 DC 78
## 9 DE 5
## 10 FL 524
## # ℹ 43 more rows
## # A tibble: 2,574 × 2
## zip_code provider_count
## <chr> <int>
## 1 00603 3
## 2 00612 15
## 3 00617 1
## 4 00622 3
## 5 00623 12
## 6 00627 1
## 7 00641 3
## 8 00646 2
## 9 00652 1
## 10 00656 2
## # ℹ 2,564 more rows
The provided data offers an overview of the number of providers
(provider_count) in each state or region
(state_cd.before). Here’s a breakdown of some key
observations and interpretations:
The provided data shows the number of healthcare providers
(provider_count) available in different zip codes
(zip_code). Here are key observations and
interpretations:
Some zip codes, particularly those in neighboring U.S. territories or smaller regions, may not display city names on the chart.